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Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare

Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare

Ned Kock, Jacques Verville
Copyright: © 2012 |Volume: 7 |Issue: 1 |Pages: 18
ISSN: 1555-3396|EISSN: 1555-340X|EISBN13: 9781466612433|DOI: 10.4018/jhisi.2012010104
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MLA

Kock, Ned, and Jacques Verville. "Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare." IJHISI vol.7, no.1 2012: pp.46-63. http://doi.org/10.4018/jhisi.2012010104

APA

Kock, N. & Verville, J. (2012). Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare. International Journal of Healthcare Information Systems and Informatics (IJHISI), 7(1), 46-63. http://doi.org/10.4018/jhisi.2012010104

Chicago

Kock, Ned, and Jacques Verville. "Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare," International Journal of Healthcare Information Systems and Informatics (IJHISI) 7, no.1: 46-63. http://doi.org/10.4018/jhisi.2012010104

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Abstract

This paper makes an important methodological contribution regarding the use of free questionnaires, illustrated through a study that shows that a healthcare professional’s propensity to use electronic communication technologies creates opportunities for interaction with other professionals, which would not otherwise be possible only via face-to-face interaction. This in turn appears to increase mutual trust, and eventually improve the quality of group outcomes. Free questionnaires are often used by healthcare information management researchers. They yield datasets without clear associations between constructs and related indicators. If such associations exist, they must first be uncovered so that indicators can be grouped within latent variables referring to constructs, and structural equation modeling analyses be conducted. A novel methodological contribution is made here through the proposal of an anchor variable approach to the analysis of free questionnaires. Unlike exploratory factor analyses, the approach relies on the researcher’s semantic knowledge about the variables stemming from a free questionnaire. The use of the approach is demonstrated using the multivariate statistical analysis software WarpPLS 2.0. The study leads to a measurement model that passes comprehensive validity, reliability, and collinearity tests. It also appears to yield practically relevant and meaningful results.

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